Associations between body composition profile and hypertension in different fatty liver phenotypes

Front Endocrinol (Lausanne). 2023 Nov 28:14:1247110. doi: 10.3389/fendo.2023.1247110. eCollection 2023.

Abstract

Background: It is currently unclear whether and how the association between body composition and hypertension varies based on the presence and severity of fatty liver disease (FLD).

Methods: FLD was diagnosed using ultrasonography among 6,358 participants. The association between body composition and hypertension was analyzed separately in the whole population, as well as in subgroups of non-FLD, mild FLD, and moderate/severe FLD populations, respectively. The mediation effect of FLD in their association was explored.

Results: Fat-related anthropometric measurements and lipid metabolism indicators were positively associated with hypertension in both the whole population and the non-FLD subgroup. The strength of this association was slightly reduced in the mild FLD subgroup. Notably, only waist-to-hip ratio and waist-to-height ratio showed significant associations with hypertension in the moderate/severe FLD subgroup. Furthermore, FLD accounted for 17.26% to 38.90% of the association between multiple body composition indicators and the risk of hypertension.

Conclusions: The association between body composition and hypertension becomes gradually weaker as FLD becomes more severe. FLD plays a significant mediating role in their association.

Keywords: association; body composition; fatty liver disease; hypertension; lipid; mediation analysis; obesity; phenotype.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Body Composition
  • Humans
  • Hypertension* / epidemiology
  • Non-alcoholic Fatty Liver Disease* / epidemiology
  • Phenotype
  • Ultrasonography

Grants and funding

This study was jointly supported by the National Natural Science Foundation of China (grant number: 82103923); Natural Science Foundation of Fujian Province (grant number: 2022J01711); Government of Fuqing City (grant number: 2019B003); Fujian Provincial Department of Science and Technology, China (grant number: 2019Y9021); and High-Level Talents Research Start-up Project of Fujian Medical University (No. XRCZX2017035 and No. XRCZX2020034).